Novel Scalable Multiphase Autonomous Vehicle Systems for Emerging Markets

Overview

Autonomous vehicle (AV) research has focused on structured, high-income Western environments, leaving dense, infrastructure-variable developing regions underexplored. This project develops three prototypes for emerging market AV technology. The goals were: I. to interpret unstructured traffic patterns, multimodal communication, and diverse road users; II. to demonstrate such data interpretation and realistic powertrain commands through a scaled robot car; and III. to recreate representative unstructured traffic environments in a virtual simulation to train and test AV control software. First, four data collection modules were designed to capture synchronized video, audio, and inertial data from real vehicles, enabling large-scale multimodal sensing in complex urban environments. Second, an 18-inch autonomous robot car was designed in SolidWorks, machined from aluminum and 3D printed, and integrated with Raspberry Pis and DC motors to model a full-scale autonomous SUV. Third, a virtual simulation environment was created in BeamNG.tech to replicate unstructured conditions, generate synthetic datasets, and evaluate autonomy algorithms. Each phase underwent iteration through calibration, deployment, and redesign. The data collection modules collected 114 hours (380 GB) of multimodal data while deployed in Kolkata, India, with reliable synchronization and post-processing, including distance prediction and object detection. The autonomous robot car achieved realistic vehicle movement, stable navigation across varied surfaces, and the ability to translate perception outputs into motion vectors and steering commands. The virtual simulation produced synthetic datasets and demonstrated the efficacy of novel path-planning and perception models. The Kolkata dataset and synthetic data were published to expand global data availability. The system validates a pipeline for developing autonomous vehicles in emerging markets, contributing to global AV research.

Competition history

• CSEF 2026 Applied Mechanics (Senior Division) · Entry S-02-29

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